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testInstruments.py
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testInstruments.py
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import pickle
import numpy as np
import pygsti
from pygsti.models import modelconstruction
from pygsti.modelpacks.legacy import std1Q_XYI as std
from ..testutils import BaseTestCase, temp_files
# This class is for unifying some models that get used in this file and in testGateSets2.py
class InstrumentTestCase(BaseTestCase):
def setUp(self):
#Add an instrument to the standard target model
self.target_model = std.target_model()
E = self.target_model.povms['Mdefault']['0']
Erem = self.target_model.povms['Mdefault']['1']
Gmz_plus = np.dot(E,E.T)
Gmz_minus = np.dot(Erem,Erem.T)
self.target_model.instruments['Iz'] = pygsti.modelmembers.instruments.Instrument({'plus': Gmz_plus, 'minus': Gmz_minus})
self.povm_ident = self.target_model.povms['Mdefault']['0'] + self.target_model.povms['Mdefault']['1']
self.mdl_target_wTP = self.target_model.copy()
self.mdl_target_wTP.instruments['IzTP'] = pygsti.modelmembers.instruments.TPInstrument({'plus': Gmz_plus, 'minus': Gmz_minus})
super(InstrumentTestCase, self).setUp()
def testFutureFunctionality(self):
#Test instrument construction with elements whose gpindices are already initialized.
# Since this isn't allowed currently (a future functionality), we need to do some hacking
E = self.target_model.povms['Mdefault']['0']
InstEl = pygsti.modelmembers.operations.FullArbitraryOp(np.dot(E, E.T))
InstEl2 = InstEl.copy()
nParams = InstEl.num_params # should be 16
I = pygsti.modelmembers.instruments.Instrument({},
evotype='default',
state_space=pygsti.baseobjs.statespace.default_space_for_udim(2))
#TODO later: add tests to appending elements to an instrument
#OLD REMOVE: No need to test this anymore - _build_paramvec has been removed
#InstEl.set_gpindices(slice(0,16), I)
#InstEl2.set_gpindices(slice(8,24), I) # some overlap - to test _build_paramvec
#
## TESTING ONLY - so we can add items!!!
#I._readonly = False
#I['A'] = InstEl
#I['B'] = InstEl2
#I._readonly = True
#
#I._paramvec, I._paramlbls = I._build_paramvec()
# # this whole test was to exercise this function's ability to
# # form a parameter vector with weird overlapping gpindices.
#self.assertEqual( len(I._paramvec) , 24 )
def testInstrumentMethods(self):
v = self.mdl_target_wTP.to_vector()
mdl = self.mdl_target_wTP.copy()
mdl.from_vector(v)
mdl.basis = self.mdl_target_wTP.basis.copy()
self.assertAlmostEqual(mdl.frobeniusdist(self.mdl_target_wTP),0.0)
for lbl in ('Iz','IzTP'):
v = mdl.to_vector()
gates = mdl.instruments[lbl].simplify_operations(prefix="ABC")
for igate in gates.values():
igate.from_vector(v[igate.gpindices]) # gpindices should be setup relative to Model's param vec
mdl.depolarize(0.01)
mdl.rotate((0,0,0.01))
mdl.rotate(max_rotate=0.01, seed=1234)
def testChangeDimension(self):
larger_ss = pygsti.baseobjs.ExplicitStateSpace([('L%d' % i,) for i in range(6)])
smaller_ss = pygsti.baseobjs.ExplicitStateSpace([('L%d' % i,) for i in range(3)])
mdl = self.target_model.copy()
new_gs = mdl.increase_dimension(larger_ss)
new_gs = mdl._decrease_dimension(smaller_ss)
#TP
mdl = self.target_model.copy()
mdl.set_all_parameterizations("full TP")
new_gs = mdl.increase_dimension(larger_ss)
new_gs = mdl._decrease_dimension(smaller_ss)
def testIntermediateMeas(self):
# Mess with the target model to add some error to the povm and instrument
self.assertEqual(self.target_model.num_params,92) # 4*3 + 16*5 = 92
mdl = self.target_model.depolarize(op_noise=0.01, spam_noise=0.01)
gs2 = self.target_model.depolarize(max_op_noise=0.01, max_spam_noise=0.01, seed=1234) #another way to depolarize
mdl.povms['Mdefault'].depolarize(0.01)
# Introducing a rotation error to the measurement
Uerr = pygsti.rotation_gate_mx([0, 0.02, 0]) # input angles are halved by the method
E = np.dot(mdl.povms['Mdefault']['0'].T,Uerr).T # effect is stored as column vector
Erem = self.povm_ident - E
mdl.povms['Mdefault'] = pygsti.modelmembers.povms.UnconstrainedPOVM({'0': E, '1': Erem}, evotype='default')
# Now add the post-measurement gates from the vector E0 and remainder = id-E0
Gmz_plus = np.dot(E,E.T) #since E0 is stored internally as column spamvec
Gmz_minus = np.dot(Erem,Erem.T)
mdl.instruments['Iz'] = pygsti.modelmembers.instruments.Instrument({'plus': Gmz_plus, 'minus': Gmz_minus})
self.assertEqual(mdl.num_params,92) # 4*3 + 16*5 = 92
#print(mdl)
germs = std.germs
fiducials = std.fiducials
max_lengths = [1] #,2,4,8]
glbls = list(mdl.operations.keys()) + list(mdl.instruments.keys())
lsgst_struct = pygsti.circuits.create_lsgst_circuits(
glbls,fiducials,fiducials,germs,max_lengths)
lsgst_struct2 = pygsti.circuits.create_lsgst_circuits(
mdl,fiducials,fiducials,germs,max_lengths) #use mdl as source
self.assertEqual(list(lsgst_struct), list(lsgst_struct2))
mdl_datagen = mdl
ds = pygsti.data.simulate_data(mdl, lsgst_struct, 1000, 'none') #'multinomial')
pygsti.io.write_dataset(temp_files + "/intermediate_meas_dataset.txt", ds)
ds2 = pygsti.io.read_dataset(temp_files + "/intermediate_meas_dataset.txt")
for opstr,dsRow in ds.items():
for lbl,cnt in dsRow.counts.items():
self.assertAlmostEqual(cnt, ds2[opstr].counts[lbl],places=2)
#print(ds)
#LGST
mdl_lgst = pygsti.run_lgst(ds, fiducials, fiducials, self.target_model) #, guessModelForGauge=mdl_datagen)
self.assertTrue("Iz" in mdl_lgst.instruments)
mdl_opt = pygsti.gaugeopt_to_target(mdl_lgst, mdl_datagen) #, method="BFGS")
print(mdl_datagen.strdiff(mdl_opt))
print("Frobdiff = ",mdl_datagen.frobeniusdist( mdl_lgst))
print("Frobdiff after GOpt = ",mdl_datagen.frobeniusdist(mdl_opt))
self.assertAlmostEqual(mdl_datagen.frobeniusdist(mdl_opt), 0.0, places=4)
#print(mdl_lgst)
#print(mdl_datagen)
#DEBUG compiling w/dataset
#dbList = pygsti.circuits.create_lsgst_circuits(self.target_model,fiducials,fiducials,germs,max_lengths)
##self.target_model.simplify_circuits(dbList, ds)
#self.target_model.simplify_circuits([ pygsti.circuits.Circuit(None,stringrep="Iz") ], ds )
#assert(False),"STOP"
#LSGST
results = pygsti.run_long_sequence_gst(ds, self.target_model, fiducials, fiducials, germs, max_lengths)
#print(results.estimates[results.name].models['go0'])
mdl_est = results.estimates[results.name].models['go0']
mdl_est_opt = pygsti.gaugeopt_to_target(mdl_est, mdl_datagen)
print("Frobdiff = ", mdl_datagen.frobeniusdist(mdl_est))
print("Frobdiff after GOpt = ", mdl_datagen.frobeniusdist(mdl_est_opt))
self.assertAlmostEqual(mdl_datagen.frobeniusdist(mdl_est_opt), 0.0, places=4)
#LGST w/TP gates
mdl_targetTP = self.target_model.copy()
mdl_targetTP.set_all_parameterizations("full TP")
self.assertEqual(mdl_targetTP.num_params,71) # 3 + 4*2 + 12*5 = 71
#print(mdl_targetTP)
resultsTP = pygsti.run_long_sequence_gst(ds, mdl_targetTP, fiducials, fiducials, germs, max_lengths, verbosity=4)
mdl_est = resultsTP.estimates[resultsTP.name].models['go0']
mdl_est_opt = pygsti.gaugeopt_to_target(mdl_est, mdl_datagen)
print("TP Frobdiff = ", mdl_datagen.frobeniusdist(mdl_est))
print("TP Frobdiff after GOpt = ", mdl_datagen.frobeniusdist(mdl_est_opt))
self.assertAlmostEqual(mdl_datagen.frobeniusdist(mdl_est_opt), 0.0, places=4)
def testBasicGatesetOps(self):
# This test was made from a debug script used to get the code working
model = pygsti.models.modelconstruction.create_explicit_model_from_expressions(
[('Q0',)],['Gi','Gx','Gy'],
[ "I(Q0)","X(pi/8,Q0)", "Y(pi/8,Q0)"])
# prep_labels=["rho0"], prep_expressions=["0"],
# effect_labels=["0","1"], effect_expressions=["0","complement"])
v0 = modelconstruction.create_spam_vector("0", "Q0", "pp")
v1 = modelconstruction.create_spam_vector("1", "Q0", "pp")
P0 = np.dot(v0,v0.T)
P1 = np.dot(v1,v1.T)
print("v0 = ",v0)
print("P0 = ",P0)
print("P1 = ",P0)
#print("P0+P1 = ",P0+P1)
model.instruments["Itest"] = pygsti.modelmembers.instruments.Instrument([('0', P0), ('1', P1)])
for param in ("full","full TP","CPTP"):
print(param)
model.set_all_parameterizations(param)
model.to_vector() # builds & cleans paramvec for tests below
for lbl,obj in model.preps.items():
print(lbl,':', obj.gpindices, pygsti.tools.length(obj.gpindices))
for lbl,obj in model.povms.items():
print(lbl,':', obj.gpindices, pygsti.tools.length(obj.gpindices))
for sublbl,subobj in obj.items():
print(" > ", sublbl,':', subobj.gpindices, pygsti.tools.length(subobj.gpindices))
for lbl,obj in model.operations.items():
print(lbl,':', obj.gpindices, pygsti.tools.length(obj.gpindices))
for lbl,obj in model.instruments.items():
print(lbl,':', obj.gpindices, pygsti.tools.length(obj.gpindices))
for sublbl,subobj in obj.items():
print(" > ", sublbl,':', subobj.gpindices, pygsti.tools.length(subobj.gpindices))
print("NPARAMS = ",model.num_params)
print("")
print("PICKLING")
x = model.preps #.copy(None)
p = pickle.dumps(x) #model.preps)
print("loading")
preps = pickle.loads(p)
self.assertEqual(list(preps.keys()),list(model.preps.keys()))
#p = pickle.dumps(model.effects)
#effects = pickle.loads(p)
#assert(list(effects.keys()) == list(model.effects.keys()))
p = pickle.dumps(model.operations)
gates = pickle.loads(p)
self.assertEqual(list(gates.keys()),list(model.operations.keys()))
p = pickle.dumps(model)
g = pickle.loads(p)
self.assertAlmostEqual(model.frobeniusdist(g), 0.0)
print("Model IO")
pygsti.io.write_model(model, temp_files + "/testGateset.txt")
model2 = pygsti.io.load_model(temp_files + "/testGateset.txt")
self.assertAlmostEqual(model.frobeniusdist(model2),0.0)
print("Multiplication")
gatestring1 = ('Gx','Gy')
gatestring2 = ('Gx','Gy','Gy')
p1 = np.dot( model.operations['Gy'].to_dense(), model.operations['Gx'].to_dense())
p2 = model.sim.product(gatestring1, scale=False)
p3,scale = model.sim.product(gatestring1, scale=True)
print(p1)
print(p2)
print(p3*scale)
self.assertAlmostEqual(np.linalg.norm(p1-scale*p3),0.0)
dp = model.sim.dproduct(gatestring1)
dp_flat = model.sim.dproduct(gatestring1,flat=True)
layout = model.sim.create_layout( [gatestring1,gatestring2] )
p1 = np.dot( model.operations['Gy'].to_dense(), model.operations['Gx'].to_dense() )
p2 = np.dot( model.operations['Gy'].to_dense(), np.dot( model.operations['Gy'].to_dense(), model.operations['Gx'].to_dense() ))
bulk_prods = model.sim.bulk_product([gatestring1,gatestring2])
bulk_prods_scaled, scaleVals = model.sim.bulk_product([gatestring1,gatestring2], scale=True)
bulk_prods2 = scaleVals[:,None,None] * bulk_prods_scaled
self.assertArraysAlmostEqual(bulk_prods[0],p1)
self.assertArraysAlmostEqual(bulk_prods[1],p2)
self.assertArraysAlmostEqual(bulk_prods2[0],p1)
self.assertArraysAlmostEqual(bulk_prods2[1],p2)
print("Probabilities")
gatestring1 = ('Gx','Gy') #,'Itest')
gatestring2 = ('Gx','Gy','Gy')
layout = model.sim.create_layout( [gatestring1,gatestring2] )
p1 = np.dot( np.transpose(model.povms['Mdefault']['0'].to_dense()),
np.dot( model.operations['Gy'].to_dense(),
np.dot(model.operations['Gx'].to_dense(),
model.preps['rho0'].to_dense())))
probs = model.probabilities(gatestring1)
print(probs)
p20,p21 = probs[('0',)],probs[('1',)]
#probs = model.probabilities(gatestring1, use_scaling=True)
#print(probs)
#p30,p31 = probs['0'],probs['1']
self.assertArraysAlmostEqual(p1,p20)
#assertArraysAlmostEqual(p1,p30)
#assertArraysAlmostEqual(p21,p31)
bulk_probs = model.sim.bulk_probs([gatestring1,gatestring2])
#Need to add way to force split a layout to check this:
#evt_split = evt.copy()
#new_lookup = evt_split.split(lookup, num_sub_trees=2)
#print("SPLIT TREE: new el_indices = ",new_lookup)
#probs_to_fill = np.empty( evt_split.num_final_elements(), 'd')
#model.bulk_fill_probs(probs_to_fill,evt_split,check=True)
#dProbs = model.sim.dprobs(gatestring1) #Removed this functionality (unused)
bulk_dProbs = model.sim.bulk_dprobs([gatestring1,gatestring2])
#hProbs = model.sim.hprobs(gatestring1) #Removed this functionality (unused)
bulk_hProbs = model.sim.bulk_hprobs([gatestring1,gatestring2])
print("DONE")
def testAdvancedGateStrs(self):
#specify prep and/or povm labels in operation sequence:
circuit_normal = pygsti.circuits.Circuit(('Gx',))
circuit_wprep = pygsti.circuits.Circuit(('rho0', 'Gx'))
circuit_wpovm = pygsti.circuits.Circuit(('Gx', 'Mdefault'))
circuit_wboth = pygsti.circuits.Circuit(('rho0', 'Gx', 'Mdefault'))
#Now compute probabilities for these:
model = self.target_model.copy()
probs_normal = model.probabilities(circuit_normal)
probs_wprep = model.probabilities(circuit_wprep)
probs_wpovm = model.probabilities(circuit_wpovm)
probs_wboth = model.probabilities(circuit_wboth)
print(probs_normal)
print(probs_wprep)
print(probs_wpovm)
print(probs_wboth)
self.assertEqual( probs_normal, probs_wprep )
self.assertEqual( probs_normal, probs_wpovm )
self.assertEqual( probs_normal, probs_wboth )
#now try bulk op
bulk_probs = model.sim.bulk_probs([circuit_normal, circuit_wprep, circuit_wpovm, circuit_wboth])
def testWriteAndLoad(self):
mdl = self.target_model.copy()
s = str(mdl) #stringify with instruments
for param in ('full','full TP','static'): # skip 'CPTP' b/c cannot serialize that to text anymore
print("Param: ",param)
mdl.set_all_parameterizations(param)
filename = temp_files + "/gateset_with_instruments_%s.txt" % param
pygsti.io.write_model(mdl, filename)
gs2 = pygsti.io.parse_model(filename)
self.assertAlmostEqual( mdl.frobeniusdist(gs2), 0.0 )
for lbl in mdl.operations:
self.assertEqual( type(mdl.operations[lbl]), type(gs2.operations[lbl]))
for lbl in mdl.preps:
self.assertEqual( type(mdl.preps[lbl]), type(gs2.preps[lbl]))
for lbl in mdl.povms:
self.assertEqual( type(mdl.povms[lbl]), type(gs2.povms[lbl]))
for lbl in mdl.instruments:
self.assertEqual( type(mdl.instruments[lbl]), type(gs2.instruments[lbl]))